models = specify_models(identify_outcome(death_time),
identify_treatment(statin_use))
death_unadj = estimate_ipwrisk(sta, models, labels = c("Death, unadjusted"))
make_table1(death_unadj,
sex,
race,
region,
age, obesity,
diabetes,
tobacco_use,
asthma,
hyperlipidemia,
heart_failure,
cerebrovascular_disease,
chronic_kidney_disease,
chronic_pulmonary_disease,
osteoporosis,
cancer,
ppi_use,
aspirin_use,
anti_coagulant_use,
corticosteroid_use, smd = TRUE)
models = specify_models(identify_outcome(death_time),
identify_treatment(statin_use, ~age+ sex +race))
death_agesex = estimate_ipwrisk(sta, models, labels = c("Death, age-sex adjusted"))
hist(death_agesex)
## Warning: Removed 4 rows containing missing values (geom_bar).
make_table1(death_agesex,
sex,
race,
region,
age, obesity,
diabetes,
tobacco_use,
asthma,
hyperlipidemia,
heart_failure,
cerebrovascular_disease,
chronic_kidney_disease,
chronic_pulmonary_disease,
osteoporosis,
cancer,
ppi_use,
aspirin_use,
anti_coagulant_use,
corticosteroid_use, smd = TRUE)
make_wt_summary_table(death_agesex)
models = specify_models(identify_outcome(death_time),
identify_treatment(statin_use, ~age +
sex +
race +
region +
obesity +
diabetes+
tobacco_use+
asthma+
hyperlipidemia+
heart_failure+
cerebrovascular_disease+
chronic_kidney_disease+
chronic_pulmonary_disease+
osteoporosis+
cancer+
ppi_use+
aspirin_use+
anti_coagulant_use+
corticosteroid_use))
death_bigps = estimate_ipwrisk(sta, models, labels = c("Death, fully adjusted"))
hist(death_bigps)
## Warning: Removed 4 rows containing missing values (geom_bar).
make_table1(death_bigps,
sex,
race,
region,
age,
obesity,
diabetes,
tobacco_use,
asthma,
hyperlipidemia,
heart_failure,
cerebrovascular_disease,
chronic_kidney_disease,
chronic_pulmonary_disease,
osteoporosis,
cancer,
ppi_use,
aspirin_use,
anti_coagulant_use,
corticosteroid_use, smd = TRUE)
make_wt_summary_table(death_bigps)
models = specify_models(identify_outcome(death_time),
identify_treatment(statin_use, ~age +
sex +
race +
region +
obesity +
diabetes+
tobacco_use+
asthma+
hyperlipidemia+
heart_failure+
cerebrovascular_disease+
chronic_kidney_disease+
chronic_pulmonary_disease+
osteoporosis+
cancer+
ppi_use+
aspirin_use+
anti_coagulant_use+
corticosteroid_use))
death_bigps_smr1 = estimate_ipwrisk(sta, models, wt_type = 1, labels = c("Death, adjusted, SMRW Untreated"))
death_bigps_smr2 = estimate_ipwrisk(sta, models, wt_type = 2, labels = c("Death, adjusted, SMRW Treated"))
hist(death_bigps)
## Warning: Removed 4 rows containing missing values (geom_bar).
hist(death_bigps, death_bigps_smr1, death_bigps_smr2, ncol = 3, weight = TRUE)
## Warning: Removed 12 rows containing missing values (geom_bar).
make_table1(death_bigps_smr1,
sex,
race,
region,
age, obesity,
diabetes,
tobacco_use,
asthma,
hyperlipidemia,
heart_failure,
cerebrovascular_disease,
chronic_kidney_disease,
chronic_pulmonary_disease,
osteoporosis,
cancer,
ppi_use,
aspirin_use,
anti_coagulant_use,
corticosteroid_use, side.by.side = T, smd = TRUE)
make_table1(death_bigps_smr2,
sex,
race,
region,
age, obesity,
diabetes,
tobacco_use,
asthma,
hyperlipidemia,
heart_failure,
cerebrovascular_disease,
chronic_kidney_disease,
chronic_pulmonary_disease,
osteoporosis,
cancer,
ppi_use,
aspirin_use,
anti_coagulant_use,
corticosteroid_use, side.by.side = T, smd = TRUE)
models = specify_models(identify_outcome(death_time),
identify_treatment(statin_use, ~age +
sex +
race +
region +
obesity +
diabetes+
tobacco_use+
asthma+
hyperlipidemia+
heart_failure+
cerebrovascular_disease+
chronic_kidney_disease+
chronic_pulmonary_disease+
osteoporosis+
cancer+
ppi_use+
aspirin_use+
anti_coagulant_use+
corticosteroid_use))
death_bigps_trim = estimate_ipwrisk(sta, models, labels = c("Death, adjusted, trimmed"), trim = 0.05)
hist(death_bigps_trim)
## Warning: Removed 4 rows containing missing values (geom_bar).
make_table1(death_bigps_trim,
sex,
race,
region,
age, obesity,
diabetes,
tobacco_use,
asthma,
hyperlipidemia,
heart_failure,
cerebrovascular_disease,
chronic_kidney_disease,
chronic_pulmonary_disease,
osteoporosis,
cancer,
ppi_use,
aspirin_use,
anti_coagulant_use,
corticosteroid_use, smd = TRUE)
make_wt_summary_table(death_bigps_trim)
death_bigps2 = death_bigps %>%
update_treatment(new_formula = ~. -hyperlipidemia) %>%
update_label("Drop Hyperlipidemia") %>%
re_estimate()
hist(death_bigps, death_bigps2)
## Warning: Removed 8 rows containing missing values (geom_bar).
make_table1(death_bigps2,
sex,
race,
region,
age, obesity,
diabetes,
tobacco_use,
asthma,
hyperlipidemia,
heart_failure,
cerebrovascular_disease,
chronic_kidney_disease,
chronic_pulmonary_disease,
osteoporosis,
cancer,
ppi_use,
aspirin_use,
anti_coagulant_use,
corticosteroid_use, smd = TRUE)
models = specify_models(identify_outcome(death_time))
death_overall = estimate_ipwrisk(sta, models, labels = c("Death overall"))
plot(death_overall) + ylab("Cumulative Risk") + xlab("Time in years")
models = specify_models(identify_outcome(cv_time),
identify_censoring(death_time))
cv_overall = estimate_ipwrisk(sta, models, labels = c("CV risk overall"))
plot(cv_overall) + ylab("Cumulative Risk") + xlab("Time in years")
plot(death_unadj) +
ylab("Cumulative Risk") + xlab("Time in years")
plot(death_unadj, effect_measure_type = "RD") +
ylab("Cumulative Risk Difference") + xlab("Time in years")
plot(death_unadj, death_bigps,scales = "fixed") +
ylab("Cumulative Risk") + xlab("Time in years")
plot(death_unadj, death_bigps, effect_measure_type = "RD", scales = "fixed") +
ylab("Cumulative Risk Difference") + xlab("Time in years")
plot(death_unadj, death_agesex, death_bigps, death_bigps_trim, death_bigps_smr1, death_bigps_smr2, ncol = 3, scales = "fixed") +
ylab("Cumulative Risk") + xlab("Time in years")
plot(death_unadj, death_agesex, death_bigps, death_bigps_trim, death_bigps_smr1, death_bigps_smr2, ncol = 3, effect_measure_type = "RD", scales = "fixed") +
ylab("Cumulative Risk Difference") + xlab("Time in years")
make_table2(death_unadj, death_agesex, death_bigps, death_bigps_trim, effect_measure_type = "RD", risk_time = 10)
forest_plot(death_unadj, death_agesex, death_bigps, death_bigps_trim, death_bigps_smr1, death_bigps_smr2, risk_time = 10, effect_measure_type = "RD")
make_table2(death_unadj, death_agesex, death_bigps, death_bigps_trim, effect_measure_type = "RR", risk_time = 10)
models = specify_models(identify_outcome(cv_time),
identify_censoring(death_time),
identify_treatment(statin_use))
cv_unadj = estimate_ipwrisk(sta, models, labels = c("CV Risk, unadjusted"))
plot(cv_unadj) +
ylab("Cumulative Risk Difference") + xlab("Time in years")
models = specify_models(identify_outcome(cv_time),
identify_censoring(death_time),
identify_treatment(statin_use, ~age +
sex +
race +
region +
obesity +
diabetes+
tobacco_use+
asthma+
hyperlipidemia+
heart_failure+
cerebrovascular_disease+
chronic_kidney_disease+
chronic_pulmonary_disease+
osteoporosis+
cancer+
ppi_use+
aspirin_use+
anti_coagulant_use+
corticosteroid_use))
cv_iptw_adj = estimate_ipwrisk(sta, models, labels = c("CV Risk, censoring at death, IPTW"))
plot(cv_unadj, cv_iptw_adj, scales = "fixed") +
ylab("Cumulative Risk Difference") + xlab("Time in years")
models = specify_models(identify_outcome(cv_time),
identify_censoring(death_time, ~age +
sex +
race +
region +
obesity +
diabetes+
tobacco_use+
asthma+
hyperlipidemia+
heart_failure+
cerebrovascular_disease+
chronic_kidney_disease+
chronic_pulmonary_disease+
osteoporosis+
cancer+
ppi_use+
aspirin_use+
anti_coagulant_use+
corticosteroid_use),
identify_treatment(statin_use, ~age +
sex +
race +
region +
obesity +
diabetes+
tobacco_use+
asthma+
hyperlipidemia+
heart_failure+
cerebrovascular_disease+
chronic_kidney_disease+
chronic_pulmonary_disease+
osteoporosis+
cancer+
ppi_use+
aspirin_use+
anti_coagulant_use+
corticosteroid_use))
cv_iptcw_adj = estimate_ipwrisk(sta, models, labels = c("CV Risk, cens at death, IPTCW"))
plot(cv_unadj, cv_iptw_adj, cv_iptcw_adj, scales = "fixed", ncol = 3) +
ylab("Cumulative Risk") + xlab("Time in years")
plot(cv_unadj, cv_iptw_adj, cv_iptcw_adj, effect_measure_type = "RD", overlay = TRUE, ncol = 3, scales = "fixed") +
ylab("Cumulative Risk Difference") + xlab("Time in years")
models = specify_models(identify_outcome(cv_death_time),
identify_competing_risk(cv_indicator, event_value = 1),
identify_treatment(statin_use, ~age +
sex +
race +
region +
obesity +
diabetes+
tobacco_use+
asthma+
hyperlipidemia+
heart_failure+
cerebrovascular_disease+
chronic_kidney_disease+
chronic_pulmonary_disease+
osteoporosis+
cancer+
ppi_use+
aspirin_use+
anti_coagulant_use+
corticosteroid_use))
cv_cr_adj = estimate_ipwrisk(sta, models, labels = c("CV Risk, death as comp risk, IPTW"))
plot(cv_iptcw_adj, cv_cr_adj, ncol = 2, scales = "fixed") +
ylab("Cumulative Risk Difference") + xlab("Time in years")
plot(cv_iptcw_adj, cv_cr_adj, effect_measure_type = "RD", ncol = 2, scales = "fixed") +
ylab("Cumulative Risk Difference") + xlab("Time in years")
make_table2(cv_iptcw_adj, cv_cr_adj, risk_time = 10)
models = specify_models(identify_outcome(death_time),
identify_treatment(statinpotency_use))
death_unadj_multi = estimate_ipwrisk(sta, models, labels = c("Death, by potency, unadjusted"))
make_table1(death_unadj_multi,
sex,
race,
region,
age, obesity,
diabetes,
tobacco_use,
asthma,
hyperlipidemia,
heart_failure,
cerebrovascular_disease,
chronic_kidney_disease,
chronic_pulmonary_disease,
osteoporosis,
cancer,
ppi_use,
aspirin_use,
anti_coagulant_use,
corticosteroid_use, smd = TRUE)
models = specify_models(identify_outcome(death_time),
identify_treatment(statinpotency_use, ~age +
sex +
race +
region +
obesity +
diabetes+
tobacco_use+
asthma+
hyperlipidemia+
heart_failure+
cerebrovascular_disease+
chronic_kidney_disease+
chronic_pulmonary_disease+
osteoporosis+
cancer+
ppi_use+
aspirin_use+
anti_coagulant_use+
corticosteroid_use))
death_bigps_multi = estimate_ipwrisk(sta, models, labels = c("Death, by potency, adjusted"))
hist(death_bigps_multi, cat = 1, binwidth = 0.03)
## Warning: Removed 3 rows containing missing values (geom_bar).
hist(death_bigps_multi, cat = 2, binwidth = 0.03)
## Warning: Removed 3 rows containing missing values (geom_bar).
make_table1(death_bigps_multi,
sex,
race,
region,
age, obesity,
diabetes,
tobacco_use,
asthma,
hyperlipidemia,
heart_failure,
cerebrovascular_disease,
chronic_kidney_disease,
chronic_pulmonary_disease,
osteoporosis,
cancer,
ppi_use,
aspirin_use,
anti_coagulant_use,
corticosteroid_use, smd = TRUE)
make_wt_summary_table(death_bigps_multi)
models = specify_models(identify_outcome(cv_time),
identify_censoring(death_time),
identify_treatment(statinpotency_use, ~age +
sex +
race +
region +
obesity +
diabetes+
tobacco_use+
asthma+
hyperlipidemia+
heart_failure+
cerebrovascular_disease+
chronic_kidney_disease+
chronic_pulmonary_disease+
osteoporosis+
cancer+
ppi_use+
aspirin_use+
anti_coagulant_use+
corticosteroid_use))
cv_bigps_multi = estimate_ipwrisk(sta, models, labels = c("CV Risk, by potency"))
plot(death_bigps_multi , cv_bigps_multi, ncol = 2, scales = "fixed") +
ylab("Cumulative Risk") + xlab("Time in years")
plot(death_bigps_multi , cv_bigps_multi, effect_measure_type = "RD", ncol = 2, scales = "fixed") +
ylab("Cumulative Risk Difference") + xlab("Time in years")
make_table2(death_bigps_multi , cv_bigps_multi, risk_time = 10)
models = specify_models(identify_outcome(nonadherence),
identify_treatment(statin_use),
identify_censoring(death_time))
nonadherence_overall = estimate_ipwrisk(sta, models, labels = c("Nonadherence risk, unadjusted"))
plot(nonadherence_overall) + ylab("Cumulative Risk") + xlab("Time in years")
models = specify_models(identify_outcome(death_time),
identify_censoring(nonadherence),
identify_treatment(statin_use, ~age +
sex +
race +
region +
obesity +
diabetes+
tobacco_use+
asthma+
hyperlipidemia+
heart_failure+
cerebrovascular_disease+
chronic_kidney_disease+
chronic_pulmonary_disease+
osteoporosis+
cancer+
ppi_use+
aspirin_use+
anti_coagulant_use+
corticosteroid_use))
death_bigps_pp = estimate_ipwrisk(sta, models, labels = c("Death, per protocol"))
plot(death_bigps, death_bigps_pp, scales = "fixed") +
ylab("Cumulative Risk") + xlab("Time in years")
plot(death_bigps, death_bigps_pp, effect_measure_type = "RD", scales = "fixed") +
ylab("Cumulative Risk") + xlab("Time in years")
make_table2(death_bigps, death_bigps_pp, risk_time = 10)
models = specify_models(identify_outcome(cv_time),
identify_censoring(nonadherence),
identify_censoring(death_time),
identify_treatment(statin_use, ~age +
sex +
race +
region +
obesity +
diabetes+
tobacco_use+
asthma+
hyperlipidemia+
heart_failure+
cerebrovascular_disease+
chronic_kidney_disease+
chronic_pulmonary_disease+
osteoporosis+
cancer+
ppi_use+
aspirin_use+
anti_coagulant_use+
corticosteroid_use))
cv_bigps_pp = estimate_ipwrisk(sta, models, labels = c("CV, per protocol"))
plot(cv_iptw_adj, cv_bigps_pp, scales = "fixed") +
ylab("Cumulative Risk") + xlab("Time in years")
plot(cv_iptw_adj, cv_bigps_pp, effect_measure_type = "RD", scales = "fixed") +
ylab("Cumulative Risk") + xlab("Time in years")
make_table2(cv_iptcw_adj, cv_bigps_pp, risk_time = 10)